It’s official: ACL is changing its name AND its spots.
I’ve claimed several times that ACL has left its first love (analytics) and doesn’t put enough work into their flagship product, ACL Analytics.
Correction: their FORMER flagship product.
At least they are publicly admitting it finally–they NO LONGER are an ANALYTICS company!
If you are in IT, audit, or security (or any other job requiring data analysis), you should NOT be cleaning data manually.
Let me share a recent experience with you….
A young IT auditor texted me at work and asked for some Active Directory user account data that I capture automatically every week, using some scheduled ACL scripts.
If you’re not familiar with my ‘Quote of the Weak’ series, I described it briefly in About. For a list of posts in this series, see here.
Test how much you know about automation technologies by taking the job automation quiz at Financial Management magazine.
Contrary to what ACL has been touting as their new ‘robotics’ feature, it is NOT robotics process automation (RPA).
[The ‘robotics’ feature is due out later in 2018. It appears to be ACL’s latest attempt to get you to use their GRC software.]
ACL, via John Verver, defines the term this way in his RPA article: “The idea is a relatively simple one: get computers to perform tasks normally performed by humans, and cut resource and time requirements for many repetitive activities.”
To increase the amount and depth of the analytics performed, steal some agile methods, and apply them to your audits.
If you’re not familiar with agile methods, check out the first 5 topics listed here (just click Next at the bottom of each page; the topics are quick to the point and full of pictures).
Briefly, agile projects are performed in cycles, or iterations, rather than in a long, linear-waterfall fashion, which is: do all planning, then field work, then reporting. Each iteration of the project creates some value and includes feedback, which is used in the next iteration to increase the value of the project.
A while back, a reader named Kyle and I had a conversation about analytics.
It started with his reading my Excel:Basic Data Analytics post where I list a number of procedures that anyone can do in Excel.
Kyle said he was expecting some “super sophisticated process & methodology that works like magic.”
In the previous post, Create a Team for Audit Analytics? Part 2, I explored the pros and cons of expecting all auditors to develop a level of data and analytic proficiency.
These auditors would continue to do audit testing that involves analytics as well as testing that does not involve analytics. In addition to keeping up their business skills, they would be learning and upgrading their data analytic skills.
In the first post of this series, I reviewed some of the pluses and minuses of creating a dedicated analytics team.
However, a third option exists, which is sort of a hybrid between having dedicated analytic auditors doing all the analytic work and requiring everyone to increase and develop their data and analytic skills.
Let’s explore the hybrid method in this post, and wrap up the series with a few final thoughts.
This is the third post of a 3-part series…